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Voice-enabled healthcare (VEH)2.5 ECTS (englische Bezeichnung: Voice-enabled healthcare)
Modulverantwortliche/r: Björn Heismann Lehrende:
Björn Heismann
Startsemester: |
WS 2022/2023 | Dauer: |
1 Semester | Turnus: |
halbjährlich (WS+SS) |
Präsenzzeit: |
30 Std. | Eigenstudium: |
45 Std. | Sprache: |
Deutsch und Englisch |
Lehrveranstaltungen:
Inhalt:
Voice recognition, speech synthesis, sentiment analysis and natural language processing are groundbreaking technologies for improved human machine interactions. This seminar intends to give students the opportunity to get in touch with the latest technologies in this space and venture out on a literature review or prototype building journey to improve healthcare applications. The seminar features a lecture part where participants are introduced to the algorithmic background of voice and natural language processing. You are enabled to analyze literature and / or develop own prototypes of voice-enabled healthcare applications. Potential fields of application include e.g. voice-controlled interventional devices and sentiment analysis for psychiatric diseases.
Lernziele und Kompetenzen:
Objectives:
Understand science of voice recognition and natural language processing
Understand medical human interactions and medical needs
Analyze combinations of voice technologies and potential applications in medicine
Skills:
Algorithmic background of voice recognition and NLP
Literature analysis and prototype building
Advanced knowledge: Medical technology
Basic knowledge: Medicine
Organisatorisches:
Master-Studierende Medizintechnik Semester 1-3 (und andere interessierte Fachrichtungen)
Studien-/Prüfungsleistungen:
Voice-enabled healthcare (Prüfungsnummer: 76061)
(englischer Titel: Voice-enabled healthcare)
- Prüfungsleistung, Seminarleistung, benotet, 2.5 ECTS
- Anteil an der Berechnung der Modulnote: 100.0 %
- weitere Erläuterungen:
Ausarbeitung und Vortrag
- Prüfungssprache: Deutsch und Englisch
- Erstablegung: WS 2022/2023, 1. Wdh.: SS 2023
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